Enterprises have moved beyond AI curiosity, but many are still struggling to turn experimentation into measurable business value. We explore why AI adoption doesn't automatically create impact, what separates isolated pilots from scaled outcomes and how leaders can close the gap between investment, readiness and ROI. The discussion focuses on prioritising use cases against business goals, putting the right operating model and governance in place, and building the data, skills and accountability needed to move from AI activity to AI value.

What you'll walk away with:
• The use cases most clearly linked to business outcomes and measurable KPIs
• Why the maturity gap is mainly organisational, not technical
• How to track adoption and impact, retire low-value efforts quickly and scale only where business value, data readiness and organisational readiness intersect